Sequential opening multi‐jammers localisation in multi‐hop wireless network. (1st September 2018)

• Record Type: Journal Article
• Authors: Wang, Tongxiang; Liang, Tao; Fan, Jianhua; Wei, Xianglin
• Is Part Of: IET information security. Volume 12:Number 5(2018)
• Page Start: 445
• Page End: 454
• Publication Date: 2018-09-01
• Subjects: radio networks -- wireless channels -- jamming -- time series -- telecommunication security; sequential opening multijammers localisation -- multihop wireless network -- MHWN -- open access -- wireless medium -- jamming attack -- wireless channel -- multiple co‐existing jammers -- multijammers localisation algorithm -- time series analysis algorithm -- received jamming signal strength -- anti jamming countermeasures -- anti jamming strategies -- MLTSA algorithm -- anomaly detection -- nodes separation; Computer security -- Periodicals; Cryptography -- Periodicals; Computer networks -- Security measures -- Periodicals; Database security -- Periodicals; 005.8
• DOI: 10.1049/iet-ifs.2017.0346
• Languages: English
• ISSNs: 1751-8709

Abstract

Abstract : Multi‐hop wireless network (MHWN) can be easily attacked by jammers for its shared nature and open access to the wireless medium. Jamming attack may pose a significant threat to MHWN by occupying wireless channel used by legitimate users. A number of anti‐jamming countermeasures have been put forward to eliminate the impact of communication disruption caused by jamming attacks. As an important building block of anti‐jamming strategies, jammer localisation attracts much attention in recent years and several algorithms have been presented. However, how to locate multiple co‐existing jammers receives little attention, and the efficiency and accuracy of the existing methods are still unsatisfactory. In this study, the authors focus on the localisation of sequential opening multi‐jammers and put forward the multi‐jammers localisation algorithm based on time series analysis (MLTSA) algorithm. The main process of MLTSA consists of four steps: detection of jamming attack, collection of received jamming signal strength, anomaly detection and separation of nodes, the existence determination and localisation of jammers. Finally, a series of simulation experiments are conducted to evaluate the correctness and effectiveness of the proposed algorithm. Experimental results show that the localisation accuracies of MLTSA are better than those of several state‐of‐the‐art solutions.